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Analyse de Redondance×Modélisation Exploratoire par Équations Structurelles×
DomainePsychométriePsychométrie
FamilleLatent structureLatent structure
Année d'origine19772009
Auteur d'origineAlbert van den WollenbergTihomir Asparouhov, Bengt Muthén
TypeAsymmetric multivariate analysisHybrid exploratory-confirmatory factor modeling
Source fondatricevan den Wollenberg, A. L. (1977). Redundancy analysis: An alternative for canonical correlation analysis. Psychometrika, 42(2), 207-219. DOI ↗Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16(3), 397-438. DOI ↗
AliasRDAESEM
Apparentées55
RésuméRedundancy Analysis (RDA) is a multivariate technique developed by van den Wollenberg (1977) that combines multiple regression and principal component analysis. RDA finds linear combinations of predictor variables that best predict variation in response variables, making it ideal for understanding how sets of predictors collectively explain multivariate outcomes.Exploratory Structural Equation Modeling (ESEM) is a hybrid approach that combines exploratory factor analysis (EFA) with confirmatory factor analysis (CFA) and path modeling, developed by Asparouhov and Muthén (2009). ESEM relaxes restrictive zero-loading assumptions of traditional CFA, allowing all indicators to load on all factors, which can reveal cross-factor complexity and improve model fit while retaining the ability to test substantive structural theories.
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ScholarGateComparer des méthodes: Redundancy Analysis · Exploratory Structural Equation Modeling. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare